High-resolution 3D spatial modelling of complex geological structures for an environmental risk assessment of abundant mining and industrial megasites

Conceptual geological models of industrial and mining megasites are an essential task of groundwater investigations as well as environmental risk assessment studies. Therefore, the conceptualization process of the structural geological model has depended on the development of a set of 2D cross-sections to portray a 3D picture of groundwater flow. This attempt always includes some simplifications that require, only to some extent, the true 3D situation of heterogeneous aquifers. Consequently, the modelled predictions of the path flow and transport conditions of contaminated groundwater are not satisfying in terms of a flow-path and risk based modelling approach. A more structured approach to develop the hydrogeological framework for the conceptual model is advocated, using different 3D geological modelling software packages to assemble the data, working in three dimensions and using this platform for subsequent groundwater flow modelling. Attention is given to the capability of different 3D modelling approaches, indicated by geostatistically based versus constructive cross-section based interpolations of complex sedimentary successions, that are compared in their results and suitability for subsequent hydrogeological modelling requirements.The paper describes the results, in high-resolution 3D modelling, of the complex geological environment of the Bitterfeld/Wolfen megasite in the eastern part of Germany. Identification, assessment, and remediation of large-scale groundwater contamination require a detailed knowledge of the heterogeneous geological structure to predict the fate and pathways of contaminants and their potential interaction with, e.g., surface water. An area of 16 km² of the model area of the Bitterfeld/Wolfen area was chosen to transfer the complex structural geological setting. The subsurface geology could be assigned to 31 lithostratigraphic units and depicted using a 10×10 m GIS grid. This constructive and “knowledge-driven” 3D modelling allows the prediction of vertical and horizontal sections, visualization purposes, volumetric calculations of distinct sedimentary units, GIS applications, and the use of the detailed digital information within the subsequent flow and transport groundwater modelling. The high-resolution digital 3D model improves the hydrogeological modelling results. It is considered a basic requirement for groundwater modelling and investigations on environmental risk and impact assessment by fate, and pathway exposure route analysis of the complex geological and groundwater situations.     

Business logic for geoprocessing of distributed geodata

This paper describes the development of a business-logic component for the geoprocessing of distributed geodata. The business logic acts as a mediator between the data and the user, therefore playing a central role in any spatial information system. The component is used in service-oriented architectures to foster the reuse of existing geodata inventories. Based on a geoscientific case study of groundwater vulnerability assessment and mapping, the demands for such architectures are identified with special regard to software engineering tasks. Methods are derived from the field of applied Geosciences (Hydrogeology), Geoinformatics, and Software Engineering.In addition to the development of a business logic component, a forthcoming Open Geospatial Consortium (OGC) specification is introduced: the OGC Web Processing Service (WPS) specification. A sample application is introduced to demonstrate the potential of WPS for future information systems.The sample application Geoservice Groundwater Vulnerability is described in detail to provide insight into the business logic component, and demonstrate how information can be generated out of distributed geodata. This has the potential to significantly accelerate the assessment and mapping of groundwater vulnerability.The presented concept is easily transferable to other geoscientific use cases dealing with distributed data inventories.Potential application fields include web-based geoinformation systems operating on distributed data (e.g. environmental planning systems, cadastral information systems, and others).     

Building a geodatabase for mapping hydrogeological features and 3D modeling of groundwater systems: Application to the Saguenay-Lac-St.-Jean region, Canada

Understanding and managing groundwater resources require the integration of a large amount of high-quality data from a variety of sources. Due to the limitations in accessing information related to groundwater and subsurface conditions, the gathering of available existing information is of crucial importance when conducting a successful hydrogeological study. Here, we present an approach for the development of an exhaustive and comprehensive groundwater database through (1) the gathering of relevant sources of information relating to groundwater, and (2) the application of a quality control process in order to screen the data for accuracy and quality. This hydrogeological database is then implemented within a GIS (geographic information system) framework coupled to a Relational Database Management System (RDBMS) as a personal geodatabase (ESRI format) GIS technology. Once established, the spatial database allows a user to request the relevant data required for a specific hydrogeological study. In addition, stratigraphic data stored within the spatial database may be utilized for constructing 3D subsurface hydrostructural models. In order to achieve this objective, the software Arc Hydro Groundwater combined with the ArcGIS spatial database is shown to be appropriate for the 3D structural representation of aquifers (groundwater reservoirs). The innovative contribution of this approach in building 3D hydrostructural subsurface models from a spatial database resides in simplifying the required step-by-step processes by considering a unified compatible combination of “RDBMS-ArcGIS-Arc Hydro Groundwater” technologies. The proposed methodology is illustrated using data from an ongoing project aimed at developing an inventory of the groundwater resources of the Saguenay-Lac-Saint-Jean region, Quebec (Canada).     

The evaluation of hydrogeological conditions in the southern part of Tamil Nadu using remote-sensing techniques

Remote-sensing techniques were employed for evaluating the hydro-geological conditions of southern districts of Tamil Nadu, India, in two phases. In the first phase a satellite remote-sensing survey was carried out during 1977-1979. This was followed by systematic groundwater investigations in the above area (phase II). Detailed studies such as aerial photo-interpretation, field investigations and ground data collection were made in four selected test sites to confirm the findings of the phase 1 regional study. The above-mentioned two-phase study provided quicker and more reliable hydrogeological information for rapid groundwater development.     

Prioritisation approach for estimating the biophysical impacts of land-use change on stream flow and salt export at a catchment scale

Predicting the impacts of land-use change on stream flow and stream salt export at a catchment scale is hampered by limited detailed measured data, particularly with regard to hydrogeological information. A recently developed modelling approach is presented that can be used to predict the variation in likely catchment response to changes in woody cover using only broadly available data. The Biophysical Capacity to Change (BC2C) model combines a downward approach for water balance, with groundwater response using groundwater flow systems (GFS) mapping to provide hydrogeological and salinity parameters, into a spatial model for estimating the impacts of changes in woody vegetation cover across large areas. The results from the model are compared to gauged flow and salinity data for 14 stream gauging stations across the Murrumbidgee catchment, in south-eastern Australia. Considering the limited calibration of the model, the results compare favourably in broad terms, and provide a useful starting point for consideration of the impacts of land-use change on stream flow and salt load, and to guide catchment managers towards areas where more detailed study can be undertaken.     

An open source Java web application to build self-contained web GIS sites

This work describes OWGIS, an open source Java web application that creates Web GIS sites by automatically writing HTML and JavaScript code. OWGIS is configured by XML files that define which layers (geographic datasets) will be displayed on the websites. This project uses several Open Geospatial Consortium standards to request data from typical map servers, such as GeoServer, and is also able to request data from ncWMS servers. The latter allows for the displaying of 4D data stored using the NetCDF file format (widely used for storing environmental model datasets). Some of the features available on the sites built with OWGIS are: multiple languages, animations, vertical profiles and vertical transects, color palettes, color ranges, and the ability to download data. OWGIS main users are scientists, such as oceanographers or climate scientists, who store their data in NetCDF files and want to analyze, visualize, share, or compare their data using a website.     

Hybrid modeling of spatial continuity for application to numerical inverse problems

A novel two-step modeling approach is presented to obtain optimal starting values and geostatistical constraints for numerical inverse problems otherwise characterized by spatially-limited field data. First, a type of unsupervised neural network, called the self-organizing map (SOM), is trained to recognize nonlinear relations among environmental variables (covariates) occurring at various scales. The values of these variables are then estimated at random locations across the model domain by iterative minimization of SOM topographic error vectors. Cross-validation is used to ensure unbiasedness and compute prediction uncertainty for select subsets of the data. Second, analytical functions are fit to experimental variograms derived from original plus resampled SOM estimates producing model variograms. Sequential Gaussian simulation is used to evaluate spatial uncertainty associated with the analytical functions and probable range for constraining variables. The hybrid modeling of spatial continuity is demonstrated using spatially-limited hydrologic measurements at different scales in Brazil: (1) physical soil properties (sand, silt, clay, hydraulic conductivity) in the 42 km² Vargem de Caldas basin; (2) well yield and electrical conductivity of groundwater in the 132 km² fractured crystalline aquifer; and (3) specific capacity, hydraulic head, and major ions in a 100,000 km² transboundary fractured-basalt aquifer. These results illustrate the benefits of exploiting nonlinear relations among sparse and disparate data sets for modeling spatial continuity, but the actual application of these spatial data to improve numerical inverse modeling requires testing.     

Borehole Optimisation System (BOS)—A GIS based risk analysis tool for optimising the use of urban groundwater

Urban groundwater is generally an underused resource, partially due to the perceived risk of pollution and the strategic difficulties in placing boreholes in built-up areas. The development of a probabilistic risk based management tool that predicts groundwater quality at potential new urban boreholes is beneficial in determining the best sites for future resource development. The Borehole Optimisation System (BOS) is a custom Geographic Information System (GIS) application that has been developed in the ArcView 3.1 environment with the objective of locating the optimum locations for new boreholes in urban areas. It couples three component models, the Catchment Zone Probability Model (CZPM), the Land-use Model (LM) and the Pollution Risk Model (PRM). The CZPM produces probabilistic catchment zones for a user-defined abstraction borehole location under uncertain and variable hydrogeological parameters. The LM identifies current and historical industries located within the selected probabilistic catchment zone. The PRM uses these industrial and the associated hydrogeological and contaminant data to predict probabilistic contaminant concentrations in a particular analysis year. This paper outlines the methodologies employed in the development of BOS and attempts to validate the approach by presenting a simulation that forecasts PCE concentrations at an actual borehole location in the Nottingham urban aquifer. The results predict contaminant levels in the abstracted water that are in agreement with observed values, both being above the UK Drinking Water Standard of 10 μg/l. These demonstrate the applicability of BOS as a tool for informing decision-makers on the development of urban groundwater resources.     

地下水空间特征自动化提取方法研究

本文在地下水水位栅格数据模型的基础上,根据地下水汇流方向、地下水降落漏斗以及地下分水岭的水文地质学含义,首先结合栅格数据的特点建立它们的数学模型,然后运用种子算法、数学形态学方法设计了自动化提取算法,并对所提取的结果进行了可视化表达。最后以苏锡常地区为例,通过对提取结果的分析,提出了该地区地下水开采应注意的一些问题。该方法有助于更好地认识地下水时空变化规律,为地下水资源管理提供辅助决策支持,同时也是数字化地下水研究的有益探索。     

Satellite remote sensing of groundwater: Quantitative modelling and uncertainty reduction using 6S atmospheric simulations

Remote sensing has been successfully used in the exploration of natural resources such as groundwater. Satellite data with different spatial, spectral and temporal characteristics have been evaluated for their potential use in groundwater detection in arid and semi-arid regions. However, distortions and noises caused by the presence of the atmosphere in the radiometric wave transmission become serious impediments for quantitative analysis and measurement work. In the present study, oasis and desert ecotone (ODE), a nonlinear ecological transitional belt, in Qira, Xinjiang Uyghur Autonomous Region of China was selected for this research. The ODE boundary was defined on the basis of widely collected information from the study area, including environmental, sociological and economic data. A model of groundwater level distribution using remote sensing (GLDRS), which empirically relates satellite sensor spectral radiance with groundwater level, is developed via in situ measurement and field examination of soil moisture and groundwater. Next, the second simulation of the satellite signal in the solar spectrum (6S), a code enabling simulations of radiative transfer process on the Sun-target-sensor path, is used to reduce uncertainties in the calculation of groundwater level. Then, groundwater level is evaluated using 6S atmospheric corrected and uncorrected Landsat-7 Enhanced Thematic Mapper (ETM)+ images respectively along with isochronous meteorological information. Greater correspondence between field examined and satellite monitoring data is obtained from 6S atmospheric corrected image (correlation coefficient is 0.94) than from the uncorrected image (correlation coefficient is 0.83).     

SOM ensemble for unsupervised outlier analysis. Application to outlier identification in the Gaia astronomical survey

Gaia is an ESA cornerstone astronomical mission that will observe with unprecedented precision positions, distances, space motions, and many physical properties of more than one billion objects in our Galaxy and beyond. It will observe all objects in the sky in the visible magnitude range from 6 to 20, up to approximately 10⁹ sources. An international scientific consortium, the Gaia Data Processing and Analysis Consortium (Gaia DPAC), has organized itself in several coordination units, with the aim, among others, of addressing the work of classifying the observed astronomical sources, using both supervised and unsupervised classification algorithms. This work focuses on the analysis of classification outliers by means of unsupervised classification. We present a novel method to combine SOMs trained with independent features that are calculated from spectrophotometry. The method as described here can help to improve the models used for the supervised classification of astronomical sources. Furthermore, it allows for data exploration and knowledge discovery in huge astronomical databases such as the upcoming Gaia mission.     

Determination of soil attribute contents by means of reflected electromagnetic energy

Remote sensing involves huge data bases of spectral reflectance in developing a new soil analysis method. The objective of this work was to use spectral reflectance data to determine the contents of physical, chemical, and mineralogical attributes of 9 soil classes with a sensor in the laboratory. To that end, a database was organized containing information on 3,300 soil samples and their respective analyses and radiometry, from the Brazilian states of São Paulo and Paraná. With the use of spectral data, multiple regression equations were obtained for 20 soil attributes. The physical and mineralogical attributes presented had, for the most part, coefficients of determination higher than 0.70, while for chemical attributes this value was, in general, smaller than 0.50. Attributes whose models obtained R² > 0.50 were tested on unknown samples that did not take part in the generation of the model. The model‐estimated soil content values of those samples were then compared with values determined in the laboratory through traditional chemical analysis. Sand, silt, clay, Fe₂O₃, SiO₂, TiO₂, Al₂O₃, Ki, and Kr presented results that were statistically similar between the estimated and determined data. The results indicated that it is possible to determine the content of these soils attributes with spectral analysis, which minimizes cost and time.     

Greening and performance relativity: An application in the shipping industry

Shipping activities involve physical movement of cargoes from production to consumption sites. Although shipping operations are beneficial to global trade as well as economic development of countries, the related activities can cause environmental harm, e.g., CO₂ emissions and ballast water discharge. As a result, public concerns about the environmental damages caused by shipping activities in servicing international trade are on the rise. To balance environmental protection and business performance improvement, shipping firms should pay more attention to the environmental and financial ramifications of their business routines. This study proposes the concept of Greening and Performance Relativity (GPR) and uses an input–output analytic approach to investigate how greening operations are related to firm performance in shipping operations. We present theory-driven arguments on the link between environmental and financial performance outcomes and empirically validate them with survey data collected from shipping firms. We also examine application of the GPR concept using survey data from the shipping industry in Hong Kong. Our analysis results show that there is a positive association between greening and firm performance in shipping operations. The results also indicate that shipping firms possess reasonably good capability in the business routines of “company policy and procedure”, “shipping documentation”, “shipping materials”, and “shipping design for compliance”.     

Using Landsat imagery interpretation for underground water prospection around Qena Province,Egypt

Abstract

This work deals with visual interpretation of Landsat satellite images covering an area of 27 000 km² around Qena Province, Upper Egypt. Geological, structural lineaments and drainage density maps are constructed. From these maps the significant hydrogeological features are extracted, correlated and utilized in locating some areas of high underground water content.     

Publishing sensor observations into Geospatial Information Infrastructures: A use case in fire danger assessment

To improve environmental monitoring, the availability of large coverage, interoperable spatio-temporal data is crucial for its integration into environmental models, for example, to compute fire danger models. In order to produce up-to-date and accurate results, these models require data with high temporal and spatial resolution. Thus, it is promising to consider the increasing number of in-situ sensors providing observations of our environment in real-time. Today, interoperable access to such spatio-temporal data is achieved by Geospatial Information Infrastructures (GIIs). From a technical point of view, GIIs provide these data through standards-based Web service interfaces. While those Web service interfaces already enable the interoperable discovery and retrieval of sensor observations, the functionality to publish sensor observations is still an arduous task. Hence, in this paper, we present an approach to improve the registration of sensors and the publication of their observations via standards-based Web service interfaces. We evaluate our approach by extending a standards-based GII and by applying the developed approach as a proof of concept to integrate in-situ weather observations into the European Forest Fire Information System for assessing fire danger in Spain.     

Large scale geospatial data conflation: A feature matching framework based on optimization and divide-and-conquer

Geospatial data conflation is the process of combining two datasets to create a better one. It has received increased research attention due to the emergence of new data sources and the need to combine information from these sources in spatial analyses. Many conflation methods exist to date, ranging from simple ones based on spatial join, to sophisticated methods based on statistics and optimization models. This paper focuses on the optimization-based conflation approach. It treats feature-matching in conflation as an optimization problem of finding a plan to match features in two datasets that minimizes the total discrepancy. Optimization based conflation methods may overcome some limitations of conventional methods, such as sub-optimality and greediness. However, they have often been deemed impractical in day-to-day analysis because they induce high computational costs (especially in combining large geospatial data).In this paper, we demonstrate the feasibility of performing optimization-based conflation for large geographic data in Geographic Information Systems. This is accomplished by utilizing efficient network flow-based conflation models and a divide-and-conquer strategy that allows the conflation models to scale to large data. Experiments show that the network-flow based model achieves average recall and precision rates of 97.7% and 90.8%, respectively in small test areas, and outperforms the traditional assignment problem by about 9% each. For larger data, it took the original network-flow model (without divide-and-conquer) nearly two days to conflate the road network in a portion of Los Angeles area near the LAX international airport. By contrast, the same model can be used to conflate the road networks of the entire Los Angeles County, CA in under 3 h with the divide and conquer strategy.     

Characterization and causes of land subsidence in Beijing,China

Long-term overexploitation of groundwater is the primary factor causing regional land subsidence in the Beijing plain area, China. Currently, large subsidence funnels exist, one each in southern and northern Beijing. We adopted the multi-temporal interferometric synthetic aperture radar (MT-InSAR) method, incorporating both persistent scatterer (PS) and small baseline (SB) approaches on 47 Envisat Advanced Synthetic Aperture Radar (ASAR) single look complex (SLC) images to map land subsidence in the Beijing plain area. The temporal and spatial variations of land subsidence and its seasonal variation were explained by the MT-InSAR results. Then, the InSAR results were combined with the dynamic monitoring of groundwater level, extensometer measurements, and hydrogeological data; the characterization and causes of land subsidence were analysed with Geographic Information System (GIS) spatial analysis methods. The results show the following. 1) Land subsidence developed rapidly in the Beijing plain area from 2003 to 2010, with obviously uneven settlement; settlement rates exceeded 100 mm year^?1 in some areas. Seasonal variation in settlement rates may be affected by changes in the precipitation rates and the exploitation of groundwater. 2) The contribution of different aquifer systems to land subsidence varies. The variation in the groundwater level in the second confined aquifer, at a depth of 100–180 m, has the greatest impact on land subsidence. 3) The settlement is centred in the lower part of the Wenyu–Chaobai and Yongding alluvial fan areas, where the compressible layer is more than 100 m thick. Meanwhile, land subsidence forms a structural feature with larger differences in the deformation gradient on both sides of faults.     

Development of the Arctic Research Mapping Application (ARMAP): Interoperability challenges and solutions

Ensuring interoperability between WebGIS applications is essential for maximizing access to data, data sharing, and data manipulation. Interoperability is maximized through the adoption of best practices, use of open standards, and utilization of spatial data infrastructure (SDI). While many of the interoperability challenges like infrastructure, data exchange, and file formats are common between applications, some regions like the Arctic present specific challenges including the need for presenting data in one or more polar projections. This paper describes the Arctic Research Mapping Application (ARMAP) suite of online interactive maps, web services, and virtual globes (the ARMAP suite; http://armap.org/) and several of the interoperability challenges and solutions encountered in development to date. ARMAP is a unique science and logistic tool supporting United States and international Arctic science by providing users with the ability to access, query, and browse information and data. Access to data services include a text-based search utility, an Internet Map Server client (ArcIMS), a lightweight Flex client, ArcGIS Explorer and Google Earth virtual globes, and Open Geospatial Consortium (OGC) compliant web services, such as Web Map Service (WMS) and Web Feature Service (WFS). Through the ARMAP suite, users can view a variety of Arctic map layers and explore pertinent information about United States Arctic research efforts. The Arctic Research Logistics Support Service (ARLSS) database is the informational underpinning of ARMAP. Avoiding duplication of effort has been a key priority in the development of the ARMAP applications. The ARMAP suite incorporates best practices that facilitate interoperability such as Federal Geographic Data Committee (FGDC) metadata standards, web services for embedding external data and serving framework layers, and open standards such as Open Geospatial Consortium (OGC) compliant web services. Many of the features and capabilities of ARMAP are expected to greatly enhance the development of an Arctic SDI.